NDLI: Decoupling power system state estimation by means of stochastic collocation

Content Provider	IEEE Xplore Digital Library
Author	Benigni, A. Liu, J. Ponci, F. Monti, A. Pisano, G. Sulis, S.
Copyright Year	2010
Description	Author affiliation: Institute for Automation of Complex Power Systems, E.ON ERC - RWTH Aachen University, Germany (Benigni, A.; Liu, J.; Ponci, F.; Monti, A.) \|\| Department of Electrical and Electronic Engineering, University of Cagliari, Italy (Pisano, G.; Sulis, S.)
Abstract	This paper presents a new approach to the problem of system decomposition in a power system state estimation problem. The complexity of power systems is growing thus challenging the way measurements for state estimation are traditionally managed. Following a previous experience in defining a decentralized solution for state estimation, the authors here propose a procedure to automatically identify how and what state information to exchange for reconstructing the state starting from partial knowledge. In particular the problem of selecting the variable that each observer has to estimate is partially solved within the framework of stochastic systems. An optimization algorithm based on dynamic programming (DP) is developed to determine the optimal set of strongly coupled variables necessary for a sufficiently accurate estimation. The developed procedure is evaluated in simulation. Preliminary results relevant to a small network are presented to show the validity of the proposed approach.
Starting Page	789
Ending Page	794
File Size	778855
Page Count	6
File Format	PDF
ISBN	9781424428328
ISSN	10915281
DOI	10.1109/IMTC.2010.5488102
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-05-03
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Power systems State estimation Stochastic systems Power system measurements Power system management Power measurement Energy management Observers Heuristic algorithms Dynamic programming Power system state estimation Decoupling of systems Decentralized estimation
Content Type	Text
Resource Type	Article
Subject	Instrumentation Electrical and Electronic Engineering

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